Corridor Mapping Using Aerial Technique

94 Pages·2012·5.05 MB·English

Final Report

FWHA/INDOT/JTRP-2006/23

CORRIDOR MAPPING USING AERIAL TECHNIQUE

By

James S. Bethel
Professor of Civil Engineering

Boudewijn H.W. van Gelder
Professor of Civil Engineering

Ali Fuat Cetin
Graduate Research Assistant

and

Aparajithan Sampath
Graduate Research Assistant

School of Civil Engineering
Purdue University

Joint Transportation Research Program
Project No: C-36-17RRR
File No: 8-4-70
SPR-2851

Conducted in Cooperation with the
Indiana Department of Transportation and the
U.S. Department of Transportation
Federal Highway Administration

The contents of this report reflect the views of the authors, who are responsible for the facts and
the accuracy of the data presented herein. The contents do not necessarily reflect the official
views or policies of the Indiana Department of Transportation or the Federal Highway
Administration at the time of publication. The report does not constitute a standard, specification,
or regulation.
Purdue University
West Lafayette, IN 47907
August 2006
TECHNICAL REPORT STANDARD TITLE PAGE

1. Report No. 2. Government Accession No. 3.Recipient’s Catalog No.
FHWA/IN/JTRP-2006/23

4. Title and Subtitle 5.Report Date
August 2006
Corridor Mapping Using Aerial Lidar Technique
6.Performing Organization Code

7. Author(s) 8. Performing Organization Report No.
James S. Bethel, Boudewijn H.W. van Gelder, Ali Fuat Cetin, Aparajithan
Sampath FWHA/INDOT/JTRP-2006/23

9. Performing Organization Name and Address 10. Work Unit No.
Joint Transportation Research Program
School of Civil Engineering
Purdue University
550 Stadium Mall 11. Contract or Grant No.
West Lafayette, IN 47907-2051 SPR-2851

12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered
Indiana Department of Transportation
State Office Building Final Report
100 North Senate Avenue
Indianapolis, IN 46204 14. Sponsoring Agency Code

15. Supplementary Notes

16. Abstract
With properly designed LIDAR control, assessment of 3D as-builts is attainable with an average over-all horizontal
(planimetric) error of 0.324 ft (9.9 cm). Specifically, with an RMS error of 0.284 ft (8.7 cm) in Northing, and 0.255 ft (7.8 cm)
in Easting. The average over-all vertical (height) error is 0.003 ft (0.1 cm) with a 0.108 ft (3.3 cm) RMS error. Lidar
recognizable control (2m x 2m chevrons) was spaced at approximately 200m parallel to the direction of the axis of the project
corridor, and at 60m sideway intervals. The project corridor was about 6 km long. Least Squares Image matching software was
developed. The internal accuracy proved to be 0.027 ft (8mm). The strip width was approximately 111m and overlap between
the Lidar strips changes from 55 to 90m sideways. Each flight line was flown twice in opposite directions showing 55 %
overlap in two strips and 75 % in other two. The overall conclusion about the usage of Lidar aerial surveys for corridor mapping
projects is that this technique is an efficient, cost cutting alternative to classical terrestrial and aerial survey techniques.
However, at this point of the research it is felt that that the design of the LiDAR control plays a critical role to the success of the
deployment of aerial LiDAR surveys. Augmentation of ground-based LiDAR and classical surveys proves necessary because of
shielding of the airborne laser signals (e.g. underpasses). Comparison of the Lidar based model against the photogrammetric
model obtained from low flying aerial photography (helicopter) should be made once the latter model becomes available.

17. Keywords 18. Distribution Statement
Airborne Lidar, Accuracy Assessment, Edge of
Pavement Feature Extraction, Evaluation

19. Security Classf. (of this report) 20. Security Classf. (of this page) 21. No. Of Pages 22. Price
89
i

TABLE OF CONTENTS

PAGE
LIST OF TABLES.............................................................................................................iii
LIST OF FIGURES...........................................................................................................iv
CHAPTER 1: INTRODUCTION........................................................................................1
1.1. Background..........................................................................................................1
1.2. Airborne Laser Scanners......................................................................................2
1.3. Research Objectives and Methodology.............................................................10
CHAPTER 2: EVALUATION AND ADJUSTMENT OF LIDAR DATA......................16
2.1. Error Sources.....................................................................................................16
2.2. Data Description................................................................................................28
2.3. Least Squares Location Model..........................................................................34
2.4. Adjusting the Uncalibrated Data.......................................................................42
CHAPTER 3: EDGE OF PAVEMENT EXTRACTION AND EVALUATION.............43
3.1. Highway Cross-Section Elements.....................................................................46
3.2. Feature Extraction..............................................................................................49
CHAPTER 4: FIELD TRIP TO ODOT.............................................................................63
CHAPTER 5: CONCLUSIONS........................................................................................69
APPENDIX A: CONTROL COMPARISION UNADJUSTED.......................................74
APPENDIX B: CONTROL COMPARISION ADJUSTED.............................................77
APPENDIX C: ELEVATION COMPARISION W/CALIBRATED DATA...................80
APPENDIX D: CONTROL POINT COMPARISION FOR EACH STRIP.....................82
ii

LIST OF TABLES
PAGE
Table 2.1: Planimetric Comparison of Lidar Data with GPS Surveyed Control Points...38
Table 2.2: Control Point Comparison in Horizontal Coordinates.....................................40
Table 3.1: Comparison of New "High Resolution" Spaceborne and Airborne
Remote Sensing Technologies........................................................................24
iii
LIST OF FIGURES
PAGE
Figure 1.1: A Typical Lidar System Sensor Configuration ...............................................3
Figure 2.1: Sensor Configuration of Airborne Lidar Systems .........................................22
Figure 2.2: Boresight Induced Errors................................................................................23
Figure 2.3: Scanner Induced Errors .................................................................................24
Figure 2.4: Illustration of the Effects of Terrain Slope on Observable Elevation Error ..27
Figure 2.5: Project Area ...................................................................................................28
Figure 2.6: Flight Paths and Control Points......................................................................29
Figure 2.7: Lidar Detectable Targets................................................................................30
Figure 2.8: Painting Lidar Detectable Targets..................................................................32
Figure 2.9: Dataset with Point Spacing for a Lidar Flight Line, Along the two
Opposing Flight Directions.............................................................................32
Figure 2.10: Final Oupout as a Lidar Intensity Image from Operator-Adjusted Data......33
Figure 2.11: Lidar Intensity and Depth Image of a Portion of the Study Area with
a 3D View.....................................................................................................33
Figure 2.12: Template and the Target in the Intensity Image for LSM............................34
Figure 2.13: One of the Control Points in the Intensity Range.........................................37
Figure 2.14: Least Squares Image Matching of Control Points........................................38
Figure 2.15: Errpr Distribution for Operator-Calibrated Data..........................................40
Figure 2.16: Lidar Points around the Control Point 267...................................................44
Figure 2.17: Lidar Data Strips Showing the Overlaps and the Directions........................41
Figure 2.18: Error Directions due to Boresight Misalignment.........................................41
Figure 3.1: Intensity Image Used for Clustering .............................................................50
Figure 3.2: Clustering Results..........................................................................................51
Figure 3.3: Closer Look at the Clustered Image ..............................................................51
Figure 3.4: Intensity Image for Stnadard Deviation Filter ...............................................53
Figure 3.5: Standard Deviation Filter Applied Intensity Image ......................................54
Figure 3.6: Entropy Filter Applied Intensity Image..........................................................55
Figure 3.7: Height Image .................................................................................................55
Figure 3.8: Standard Deviation Filter Applied Height Image ..........................................56
Figure 3.9: Threshold Application ...................................................................................57
Figure 3.10: Non-Terrain Objects.....................................................................................57
Figure 3.11: Bare Earth Pixels..........................................................................................58
Figure 3.12: Intensity Image Without Non-Terrain Objects ............................................59
Figure 3.13: Clustered Image Showing Road Surfaces ...................................................59
Figure 3.14: Separated Road Surfaces..............................................................................60
Figure 3.15: Opening and Closing Operation on Road Surfaces .....................................60
Figure 3.16: Road Surfces over Intensity Image .............................................................61
Figure 3.17: Application of Canny Edge Detection over Road Surfaces.........................61
Figure 4.1: Cessna Grand Caravan :Lidar Instrumentation..............................................64
Figure 4.2: Scenes from the Project Area Produced using QT Modeler with
Elevation Values ...........................................................................................67
Figure 4.3: Scenes from the Project Area Produced Using QT Modelier with
Intensity Values .............................................................................................68
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND
Accurate terrain mapping is important for highway corridor planning and design,
environmental impact assessment, and infrastructure asset management. The management
of transportation infrastructure assets can be more efficient and cost-effective by using a
geographical information system (GIS) for defining georeferenced locations, storing
attribute data, and displaying data on maps. Collecting good-quality geographical
coordinate data by traditional ground-based manual methods may require a substantial
investment depending upon the size of the assets. In the case of natural or orchestrated
disasters, the assessment of damage and re-building can be costly and time-consuming if
the inventory and terrain model data are not easily available. Safe and efficient mobility
of goods and people requires periodic monitoring and maintenance of all transportation
infrastructure components within the right-of-way including the following: pavements,
bridges, tunnels, interchanges, roadside safety structures, and drainage structures. These
data collection activities require time- and labor-intensive efforts. In many parts of the
world, highway data are collected at highway speed using non-contact photography,
video, laser, acoustic, radar, and infrared sensors. These terrestrial non-contact
technologies may suffer limitations resulting from time of day, traffic congestion, and
proximity to urban locations. Additionally, traditional terrestrial ground surveys can be
quite hazardous, especially in the areas of maintenance work zones. Modern airborne and
1
spaceborne remote-sensing technologies offer cost-effective terrain mapping, inventory,
and monitoring data collection [115].

Recently Airborne Laser Scanning (ALS) systems are preferred more and more for
collecting topographic data since it provides quick and accurate data for large areas.

Laser scanning systems available on the market are presently in a fairly mature state of
art, where most of technical hardware difficulties and system integration problems have
been solved. The systems are very complex, being more a ‘geodetic’ system on the data
acquisition part and more a ‘photogrammetric’ system on the data processing part. What
very much remains is the development of algorithms and methods for interpretation and
modeling of laser scanner data, resulting in useful representations and formats for an end-
user [100].

1.2 AIRBORNE LASER SCANNERS
Airborne laser mapping is an emerging technology in the field of remote sensing that is
capable of rapidly generating high-density, geo-referenced digital elevation data with an
accuracy equivalent to traditional land surveys but significantly faster than traditional
airborne surveys.
Airborne laser mapping offers lower field operation costs and post-processing costs
compared to traditional survey methods. Point for point, the cost to produce the data is
significantly less than other forms of traditional topographic data collection making it an
2
attractive technology for a variety of survey applications and data end-users requiring low
cost, high-density, high accuracy geo-referenced digital elevation data.
Airborne laser mapping use a combination of three mature technologies; rugged compact
laser rangefinders (LIDAR), highly accurate inertial reference systems (INS) and the
global positioning satellite system (GPS) (Figure 1.1) . By integrating these subsystems
in to a single instrument mounted in a small airplane or helicopter, it is possible to rapidly
produce accurate digital topographic maps of the terrain beneath the flight path of the
aircraft.

Figure 1.1 A typical LIDAR system sensor configuration

3
The absolute accuracy of the elevation data is 15 cm; relative accuracy can be less than 5
cm. Absolute accuracy of the XY data is dependent on operating parameters such as
flight altitude but is usually 10's of cm to 1 m.
The elevation data is generated at 1000s of points per second, resulting in elevation point
densities far greater than traditional ground survey methods. One hour of data collection
can result in over 10,000,000 individually geo-referenced elevation points. With these
high sampling rates, it is possible to rapidly complete a large topographic survey and still
generate DTMs with a grid spacing of 1 m or less.
The technology allows for extremely rapid rates of topographic data collection. With
current commercial systems it is possible to survey one thousand square kilometers in
less than 12 hours and have the geo-referenced DTM data available within 24 hours of
the flight. A 500 kilometer linear corridor, such as a section of coastline or a transmission
line corridor can be surveyed in the course of a morning, with results available the next
day.
Airborne laser mapping instruments are active sensor systems, as opposed to passive
imagery such as cameras. Consequently, they offer advantages and unique capabilities
when compared to traditional photogrammetry. For example, airborne laser mapping
systems can penetrate forest canopy to map the floor beneath the treetops, accurately map
the sag of electrical power lines between transmission towers or provide accurate
elevation data in areas of low relief and contrast such as beaches.
4
Airborne laser mapping is a non-intrusive method of obtaining detailed and accurate
elevation information. It can be used in situations where ground access is limited,
prohibited or risky to field crews.
Commercial airborne laser mapping systems are now available from several instrument
manufacturers while various survey companies have designed and built custom systems.
Similar to aerial cameras, the instruments can be installed in small single or twin-engine
planes or helicopters. Since the instruments are less sensitive to environmental conditions
such as weather, sun angle or leaf on/off conditions, the envelope for survey operations is
increased. In addition, airborne laser mapping can be conducted at night with no
degradation in performance.
A number of service providers are operating these instruments around the world, either
for dedicated survey needs or for hire on a project basis. Some organizations are starting
to survey areas on speculation and then offering the laser-generated data sets for resale
similar to the satellite data market.
1.2.1 The Technology
While the core technologies for airborne laser mapping have been in development for the
past 25 years, the commercial market for these instruments has only developed
significantly within the last five years. This commercial development has been driven by
the availability of rugged, low-cost solutions for each of the core subsystems and the
growing demand for cheap, accurate, timely, digital elevation data.
5